Papers Knowledge Graphs
“Knowledge Graphs” 태그가 달린 논문 3,744편 · 필터 해제
SABET-QA: Temporal Knowledge Graph Question Answering
Question Answering over Temporal Knowledge Graphs (TKGQA) requires reasoning over time-sensitive facts, yet existing embedding-based methods struggle with multi-step queries due to single-pass reasoning pipelines. We pro…
Graph Question AnsweringKnowledge GraphsG-MARK: Grounded Multi-Agent Reasoning for Cooperative Driving via Knowledge Graphs
Autonomous driving systems must operate under partial observability, where safety-critical objects may be occluded or visible only to neighboring connected vehicles. Vehicle-to-vehicle cooperation can reduce this uncerta…
Trajectory ForecastingAutonomous DrivingKnowledge GraphsMissDiag: Diagnostic Evaluation of Incomplete-Knowledge Robustness in KGQA and KG-RAG
Knowledge graph question answering (KGQA) and knowledge-graph-based retrieval-augmented generation (KG-RAG) aim to ground answers in explicit graph evidence, but real-world knowledge graphs are often sparse, outdated, an…
Graph Question AnsweringKnowledge GraphsGraphWake: Group Polarization via Memory-Mediated Polarization Cascade in LLM-Agent Communities
LLM-driven agents can autonomously exchange opinions on online platforms and form communities. Such agent-operated social platforms raise a new security concern: attackers may manipulate agents to induce group polarizati…
Knowledge GraphsGeneral Semantic Knowledge Infusion for Spatio-Temporal Traffic Forecasting
Although Graph Neural Networks (GNNs) have made significant advances in spatio-temporal traffic forecasting, their performance is limited when they rely solely on sensor proximity or road-network topology. This paper pre…
Knowledge GraphsQuipu: A Governed Bitemporal Knowledge Graph Store
Agents now write knowledge graphs, but knowledge-graph stores still carry defaults set when humans curated them: accept writes now and clean later, keep one time axis or none, treat every writer's facts as equally trustw…
Knowledge GraphsAutoSchema: Live Schema Grounding for Agentic Text-to-Sparql over Heterogeneous Knowledge Graphs
Life science knowledge graphs make large collections of structured data available through SPARQL, but each resource uses its own schema, identifiers, and links. TogoMCP helps language model agents query these resources b…
Knowledge GraphsNovel Knowledge-Guided Generative Methods for Synthetic Transcriptomic Data
As biomedical research increasingly relies on data-intensive tools, the quality and utility of datasets are critical. Challenges such as imbalances, biases, and ethical or legal constraints often limit access to high-qua…
Synthetic Data GenerationGraph Neural NetworkKnowledge GraphsWhen Your Agent Opens the Chat App: Agent-Controlled Search over Raw Chat Logs Rivals Structured Memory
Agent-memory systems increasingly buy retrieval quality with structure, transforming raw conversation histories into summaries, embeddings, trees, or knowledge graphs before any question is asked. We ask how much of that…
Knowledge GraphsSAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges
While retrieval-augmented generation (RAG) has proven effective at giving LLMs access to external knowledge, mainstream dense-retrieval implementations remain inherently limited in handling structured constraints and mul…
Knowledge GraphsImproving Interoperability among Defence and National Security Ontologies: Analysis and Evaluation Tasks
The use of ontologies and knowledge graphs is becoming increasingly widespread in the defence and national security domain. Numerous ontologies have been developed through initiatives led by academia, industry, and gover…
Knowledge GraphsViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion
Knowledge graph completion (KGC) aims to infer missing entities or relations from incomplete graph structures, and has evolved into multimodal knowledge graph completion (MMKGC), where entities are associated with multip…
Knowledge Graph CompletionRepresentation LearningMultimodal ReasoningKnowledge GraphsFully Inductive Cardinality Estimation
Query optimization of Basic Graph Patterns (BGP) SPARQL queries over Knowledge Graphs (KG) requires accurate cardinality estimation. Recently published learned estimators outperform statistics- and sampling-based approac…
Graph Neural NetworkKnowledge GraphsGGC: Selective Query Correction for Reliable Text-to-SPARQL Generation
Large language models (LLMs) have demonstrated strong capabilities in structured query generation, making them a natural choice for Text-to-SPARQL, which translates natural language questions into executable SPARQL queri…
Knowledge GraphsSciSchema.org: A Multidisciplinary Collection of Schemas for Structured Scientific Process Descriptions
Scientific processes are often described in heterogeneous article discourse, with details needed for comparison, reproducibility, reuse, and automation dispersed across prose, tables, figures, protocols, and supplementar…
Information ExtractionKnowledge GraphsGLM-RAG: Graph Language Models for Graph-Based Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) over knowledge graphs requires retrievers that can effectively capture both graph structure and semantic information. Recent approaches have explored graph neural network (GNN)-based …
Graph Neural NetworkKnowledge GraphsDual-Path LLM Reasoning for Multimodal Few-Shot Knowledge Graph Completion
Knowledge graph completion (KGC) aims to infer missing facts in knowledge graphs (KGs), thereby improving their completeness and supporting downstream intelligent applications. However, emerging entities and relations in…
Knowledge Graph CompletionKnowledge GraphsDetecting Knowledge Inconsistencies Across Text, Tables, and Knowledge Graphs
Wikipedia and Wikidata are widely used for information access, LLM pre-training, and retrieval-augmented generation. Their knowledge is deeply connected but scattered across text, tables, and knowledge graphs. This raise…
Knowledge GraphsIRIS: Reusable Identity Representations from Frozen LLMs for Entity Alignment
Entity alignment (EA) identifies entities across knowledge graphs (KGs) that refer to the same real-world object. Conventional EA methods mainly exploit explicit graph structures and textual fields, which often provide i…
Entity AlignmentKnowledge GraphsFrom Static Bibliometrics to Dynamic Knowledge Graphs: An LLM-Powered Framework for Modernizing Science, Technology, and Innovation (STI) Analytics
Bibliometric indicators - citation counts, h-indexes, co-authorship networks - have long anchored science, technology, and innovation (STI) analytics, yet suffer from temporal lag, semantic shallowness, and an inability …
Knowledge Graphs